ASSESSING HYPERSPECTRAL VEGETATION INDICES FOR ESTIMATING LEAF CHLOROPHYLL CONCENTRATION OF SUMMER BARLEY

Hyperspectral reflectance data were collected at 7 critical phenological stages in a summer barley field with 7 varieties in 2010, without artificial nutrient gradients. Throughout the range of 350 to 1800 nm, all possible two-bands combinations for the simple ratio (SR = R<i>j</i>/R<...

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Main Authors: K. Yu, V. Lenz-Wiedemann, G. Leufen, M. Hunsche, G. Noga, X. Chen, G. Bareth
Format: Article
Language:English
Published: Copernicus Publications 2012-07-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-7/89/2012/isprsannals-I-7-89-2012.pdf
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spelling doaj-90327930ee57483a855f04620cd1fbdf2020-11-24T21:45:06ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502012-07-01I-7899410.5194/isprsannals-I-7-89-2012ASSESSING HYPERSPECTRAL VEGETATION INDICES FOR ESTIMATING LEAF CHLOROPHYLL CONCENTRATION OF SUMMER BARLEYK. Yu0V. Lenz-Wiedemann1G. Leufen2M. Hunsche3G. Noga4X. Chen5G. Bareth6Institute of Geography (GIS & Remote Sensing Group), University of Cologne, 50923 Köln, GermanyInstitute of Geography (GIS & Remote Sensing Group), University of Cologne, 50923 Köln, GermanyINRES- Horticultural Science, University of Bonn, 53121 Bonn, GermanyINRES- Horticultural Science, University of Bonn, 53121 Bonn, GermanyINRES- Horticultural Science, University of Bonn, 53121 Bonn, GermanyCollege of Resources & Environmental Sciences, China Agricultural University, 100094 Beijing, ChinaInstitute of Geography (GIS & Remote Sensing Group), University of Cologne, 50923 Köln, GermanyHyperspectral reflectance data were collected at 7 critical phenological stages in a summer barley field with 7 varieties in 2010, without artificial nutrient gradients. Throughout the range of 350 to 1800 nm, all possible two-bands combinations for the simple ratio (SR = R<i>j</i>/R<i>i</i>) and the normalized difference vegetation index (NDVI = (R<i>j</i>&minus;R<i>i</i>)/(R<i>j</i>+R<i>i</i>)) were evaluated using linear regression analysis against the leaf chlorophyll concentration (LCC). This study introduces a more comprehensive way of using the "correlation matrix" method for selecting sensitive bands and shows that in this way the newly selected SRs may outperform the NDVIs for estimating LCC. With this method, the selection of two-bands combinations for the SRs and NDVIs improved the performance for estimating LCC. Both the new SR (734, 629) and the new NDVI (667, 740) explained more than 74% of the variation in LCC across all the growth stages and all varieties. Compared with published indices, newly selected SRs and NDVIs improved the predictive ability for LCC. The most significant improvement was observed with increasing of <i>R<sup>2</sup></i> values by 13% for SR and 6% for NDVI. The overall performances of both newly selected indices and published indices were significantly influenced by the varieties. Moreover, Ultraviolet, Violet and Blue bands are more effective for estimating the LCC for a single variety, whereas Red-edge bands are more effective for that across all varieties. Therefore, a conclusion can be drawn that selecting twobands combinations significantly improves the capability of SRs and NDVIs for estimating the LCC of summer barley.http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-7/89/2012/isprsannals-I-7-89-2012.pdf
collection DOAJ
language English
format Article
sources DOAJ
author K. Yu
V. Lenz-Wiedemann
G. Leufen
M. Hunsche
G. Noga
X. Chen
G. Bareth
spellingShingle K. Yu
V. Lenz-Wiedemann
G. Leufen
M. Hunsche
G. Noga
X. Chen
G. Bareth
ASSESSING HYPERSPECTRAL VEGETATION INDICES FOR ESTIMATING LEAF CHLOROPHYLL CONCENTRATION OF SUMMER BARLEY
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet K. Yu
V. Lenz-Wiedemann
G. Leufen
M. Hunsche
G. Noga
X. Chen
G. Bareth
author_sort K. Yu
title ASSESSING HYPERSPECTRAL VEGETATION INDICES FOR ESTIMATING LEAF CHLOROPHYLL CONCENTRATION OF SUMMER BARLEY
title_short ASSESSING HYPERSPECTRAL VEGETATION INDICES FOR ESTIMATING LEAF CHLOROPHYLL CONCENTRATION OF SUMMER BARLEY
title_full ASSESSING HYPERSPECTRAL VEGETATION INDICES FOR ESTIMATING LEAF CHLOROPHYLL CONCENTRATION OF SUMMER BARLEY
title_fullStr ASSESSING HYPERSPECTRAL VEGETATION INDICES FOR ESTIMATING LEAF CHLOROPHYLL CONCENTRATION OF SUMMER BARLEY
title_full_unstemmed ASSESSING HYPERSPECTRAL VEGETATION INDICES FOR ESTIMATING LEAF CHLOROPHYLL CONCENTRATION OF SUMMER BARLEY
title_sort assessing hyperspectral vegetation indices for estimating leaf chlorophyll concentration of summer barley
publisher Copernicus Publications
series ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 2194-9042
2194-9050
publishDate 2012-07-01
description Hyperspectral reflectance data were collected at 7 critical phenological stages in a summer barley field with 7 varieties in 2010, without artificial nutrient gradients. Throughout the range of 350 to 1800 nm, all possible two-bands combinations for the simple ratio (SR = R<i>j</i>/R<i>i</i>) and the normalized difference vegetation index (NDVI = (R<i>j</i>&minus;R<i>i</i>)/(R<i>j</i>+R<i>i</i>)) were evaluated using linear regression analysis against the leaf chlorophyll concentration (LCC). This study introduces a more comprehensive way of using the "correlation matrix" method for selecting sensitive bands and shows that in this way the newly selected SRs may outperform the NDVIs for estimating LCC. With this method, the selection of two-bands combinations for the SRs and NDVIs improved the performance for estimating LCC. Both the new SR (734, 629) and the new NDVI (667, 740) explained more than 74% of the variation in LCC across all the growth stages and all varieties. Compared with published indices, newly selected SRs and NDVIs improved the predictive ability for LCC. The most significant improvement was observed with increasing of <i>R<sup>2</sup></i> values by 13% for SR and 6% for NDVI. The overall performances of both newly selected indices and published indices were significantly influenced by the varieties. Moreover, Ultraviolet, Violet and Blue bands are more effective for estimating the LCC for a single variety, whereas Red-edge bands are more effective for that across all varieties. Therefore, a conclusion can be drawn that selecting twobands combinations significantly improves the capability of SRs and NDVIs for estimating the LCC of summer barley.
url http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-7/89/2012/isprsannals-I-7-89-2012.pdf
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